Download Central Bank Independence and Political Pressure in the

14020-EEF
Central Bank Independence and
Political Pressure in the
Greenspan Era.
Gerard H. Kuper
Jan Hessel Veurink
1
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2
Central Bank Independence and Political Pressure
in the Greenspan Era
Gerard H. Kuper
Faculty of Economics and Business, University of Groningen
Jan Hessel Veurink
Faculty of Economics and Business, University of Groningen
3
Central Bank Independence and Political Pressure in the
Greenspan Era
Gerard H. Kupera and Jan Hessel Veurinkb
July 2014
Abstract: This paper investigates whether political pressure from incumbent
presidents influences the Fed’s monetary policy during the period that Alan Greenspan
was the chairman of the United States Federal Reserve Board. A modified Taylor rule
- featuring the inflation rate and the unemployment gap rather than the output gap with time-varying coefficients will be used to test well-known political-economic
theories of Nordhaus (1975) and Hibbs (1987). This novel approach addresses some of
the disadvantages of Ordinary Least Squares, and has the additional benefit of
allowing the use of mixed frequency data. Our findings suggest that the Fed under
Greenspan did not create election driven monetary cycles, but was less inflation avers
with a Democratic president.
Keywords: Taylor rule, political business cycles, state space, time-varying coefficients
JEL classifications: E42, E47, E58
_________________________________
a
Corresponding author: G.H. Kuper, Department of Economics, Econometrics and
Finance, University of Groningen, PO Box 800, 9700 AV Groningen, The
Netherlands, email: [email protected], tel. +31 50 3633756, fax. +31 50 3637337.
b
MSc Economics student at the VU University, Amsterdam.
1.
Introduction
In the recent years, economists and policy makers have shown interest in independent
central banks and their monetary policy, and a number of countries increased the legal
independence of their central banks. There are several reasons for the trend towards
more independence of central banks since the breakdown of the Bretton Woods
system. Especially the success of the independent Bundesbank led to the belief that
independence of the central bank is a useful devise to maintain price stability.
Furthermore, the Maastricht Treaty requires that having an independent central bank is
a condition for entering the Economic and Monetary Union. Also for former socialist
countries an independent central bank is a good start for a well-functioning market
economy.
Central bank independence seems beneficial in the long run. However, policy
makers could have other objectives. Kiewiet and Rivers (1984) find a relationship
between the actual economic performance of a country and upcoming elections. The
authors claim that voters are more likely to support the incumbent party when the
economic situation is more favorable. Consequently, politicians might try to influence
the behavior of the central bank.
In this paper we focus on the period in which the Fed was chaired by Greenspan.
In this period some authors argue that Greenspan, and also other central bankers,
departed from a strict or rules-based monetary policy rule because of favourable or
less favourable economic circumstances. For instance Cargill and O’Driscoll (2012)
argues that interest rates lower than predicted by the Taylor rule contributed to the runup of real estate prices, the burst of the US bubble economy and subsequent
international financial crisis in late 2008 and early 2009. Also more recently central
banks are not free of political pressure, because to resolve the global financial crisis
pressure increased on central banks to shift to an activist policy to support fiscal
imbalances and prop up troubled financial institutions.
This paper investigates whether political pressure from the incumbent has had an
effect on monetary policy in the United States in the period August 1987 until and
including January 2006. Cargill and O’Driscoll (2013) concludes that Fed’s emphasis
on the short run inevitably subjects them to political pressure. We develop a modified
Taylor rule and test the two main theoretical findings of political influence on
macroeconomic policy from Nordhaus (1975) and Hibbs (1987) which will be
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reviewed in the next section. We present the econometric model of the Taylor rule in
Section 3. In this section we also discuss how we test our hypothesis related to
political pressure. The data is presented in Section 4. Section 5 discussed our results.
In Section 6 we test whether there is political pressure on the Fed. We complete the
paper with our main conclusion in Section 7.
2.
Literature review
The time inconsistency, or dynamic inconsistency, problem is the main theoretical
driver for central bank independence. Time inconsistency in economics occurs when a
present plan is optimal for a future period but is actually suboptimal when the future
period starts. The most prominent models, based on game theory, of the dynamic
inconsistency approach are from Kydland and Prescott (1997) and Barro and Gordon
(1983). Their conclusion is almost universally that the dynamic inconsistency problem
leads to a bias towards higher inflation. As a result Rogoff (1985) concludes that the
central bank’s objective function should reflect stronger inflation aversion than the
objective function of the society. In other words, society is better off by appointing a
conservative central banker that has a different objective function then the social
welfare function. This makes central bank independence theoretically a preferred
option. Note however that there is a discussion what central bank independence is, and
whether it is a necessary condition for price stability. Taylor (2013) concludes that
formal independence without policy rules does not generate good
policy outcomes. We refer to Hayo and Hefeker (2002) for a critical review of the
literature.
The literature on time inconsistency and central bank independence focuses on
price stability as a prerequisite for growth. However, the relationship between inflation
and economic growth is complex, but most economists agree that inflation negatively
influences economic growth due to for instance uncertainty in the markets, menu costs
and disinflation costs. This is supported by early empirical research of Fischer (1993)
and Barro (1998). Alesina and Summer (1993), Grilli et al. (1991), and Cukierman et
al. (1992) conclude that central bank independence is negatively correlated with
inflation. For a survey of we refer to Temple (2000). Although these results suggest
that central bank independence has positive effects on real economic performance, the
empirical results are not clear-cut. Both Alesina and Summers (1993) and Cukierman
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et al. (1993) do not find any relationship between real economic variables and legal
central bank independence.
We focus in this paper on political pressure on monetary and fiscal authorities.
Barro and Gordon (1983) argue that when monetary rules are in place, every period
the policy maker is tempted to cheat on the monetary rules in order to benefit from
inflation shocks. A politician wants to engage in monetary policy and fiscal policy in
order to satisfy his own or his constituents’ preferences instead of choosing the
optimal solution for society. One of the possible arguments for choosing a suboptimal
solution is mentioned by Nordhaus (1975), who argues that politicians only care about
staying in the office. The main supporting assumption of his model is that voters are
not forward looking and do not have any memory and therefore can be systematically
fooled. Nordhaus’ (1975) model led to the creation of a political business cycle (PBC),
where the incumbent reduces unemployment before the elections by stimulating the
economy and will fight inflation right after the economy by causing a recession.
Although the outcomes of this model became quite famous, the main critique is based
on the assumption that voters are not rational. However, by including rational voters
Cukierman and Meltzer (1986) and Rogoff and Sibert (1988) arrived at similar
conclusions. In Rogoff and Sibert (1988) the incomplete information of voters on the
competence of policy makers caused the cycle, while in Cukierman and Meltzer
(1986) policymakers and voters have different information about shocks. However, in
many econometric studies on PCB’s such as Alesina et al. (1997) and Faust and Irons
(1999) there is little support for increasing economic activity prior to elections in the
United States.
There is also a different view on why politicians would like to deviate from the
optimal solution. Hibbs (1987) argues that there are ideological differences between
parties and this will lead to partisan politics creation partisan macroeconomic cycles.
For the United States, his main assumption was that Democratic voters are poor and
laborers, while the Republican voters are rich and capitalists. In addition, he claims
that expansionary fiscal and monetary policy will lead to income redistribution from
the rich to the poor. Therefore, Hibbs concludes that the Democrats would be more
tolerant to higher inflation rates, while the Republicans would be more inflation
averse. Alesina (1987) models the partisan approach of Hibbs (1987) in a rational
world, where elections create uncertainty because the rational economic agents do not
know which party will win. As a result, this model predicts only differences at the
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beginning of the term in office of the new party. In the case of the United States, it
predicts that if the Republicans win the election there will be low money growth and a
recession while economic growth and high money growth will be observed when the
Democrats win the election. Alesina and Sachs (1988) empirically confirm the
findings of Alesina (1987).
Most empirical research about the PBC and the partisan approach have focused
on both monetary as fiscal policy. However, the fiscal authority is shared between the
incumbent and the congress in the United States and the president has little influence
in the congress. As a result, it is difficult for the president to manipulate the economy
with fiscal policy. Therefore, the literature focuses on political monetary cycles. In the
early search for political monetary cycles - explained by electorally motivated
incumbents as in the Nordhaus (1975) model - McCallum (1978), Beck (1984) and
Havrilesky (1987) find no evidence for political monetary cycles, while Grier (1984)
did find a political monetary cycle by looking at M1. The latter result is confirmed by
Beck (1987). However, Beck (1987) argues that there could be a political cycle in M1,
which is not created by the Fed because M1 is not under direct control of the Fed. In
other words, M1 is an endogenous variable. He suggests to look at the instruments of
the Fed such as the federal funds rate to find evidence for a political monetary cycle.
In those instruments, he does not find a political cycle. Nevertheless, Grier (1989) who
controls for GNP, interest rates and budget deficits does find a cycle in M1. The
empirical evidence on the opportunistic political monetary cycles thus has obtained
mixed results, so Grier (1989) concludes that the ‘case is not closed.’ A recent paper
by Abrams and Iossifov (2006) does find a political monetary cycle in the federal
funds rate when the president and the chairman of the Fed share the same partisan
affiliation.
Although the election driven monetary cycles gave mixed results, there is more
positive empirical evidence for the partisan theory. Chappell et al. (1993) finds that the
presidents exerted their partisan’s influences in the Presidential appointments with the
Federal Open Market Committee (FOMC). Democrats’ appointees of the FOMC are
less tight in monetary policy making then Republicans making the Presidential
appointments a channel to influence their partisan affiliations. Moreover, Chappell and
Keech (1986) find that the money growth is systematically higher under Democratic
presidents, which means that Democrats care less about inflation. Furthermore,
Caporale and Grier (1998) state that with Republican presidents there is significantly
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tighter monetary policy. In accordance to Caporale and Grier (1998), Corder (2006)
claims that with a backward-looking Taylor rule the Fed is more an inflation fighter
with Republicans in the White House. To conclude, it seems that the President still has
partisan influence on Fed decision-making based on previous empirical studies.
As a final remark we note that both Abrams and Iossifov (2006) and Corder
(2006) test the theories of political pressure of the Fed by a Taylor rule, which will
also be used in this paper. In a comment Tempelman (2007) argues that the time
period (1954-2004) in the paper of Abrams and Iossifov (2006) is too long obscuring
trends like the improvement in monetary policy over the last 30 years. We also use a
relatively short time period (1987-2006), but unlike Corder (2006) and Abrams and
Iossifov (2006) we use a forward-looking model. More details on our Taylor
specification will be given in the next section.
3. Economic model
3.1 Time-varying Taylor rule
To test the political monetary cycle theory and the partisan theory we use a timevarying version of a modified Taylor rule model for Fed’s behavior. The standard rule
from Taylor (1993) can be written as the following linear equation:
= + ∗ + − ∗ + − ∗ (1)
Here, represents the nominal short term interest rate, is the inflation rate, ∗ is the
equilibrium real interest rate, ∗ is the target level of the inflation rate, is the natural
logarithm of GDP, ∗ is the natural logarithm of potential GDP. The difference
between the loglevel of GDP and the loglevel of potential GDP is the output gap. The
coefficients and measure the reaction of the Fed when inflation and output
deviates from the target inflation rate and potential GDP, respectively. Both and are positive (Taylor, 1993 proposes = 0.5; = 0.5). The rational is that when the
inflation exceeds its target or when the output gap is positive, the nominal interest rate
has to be increased in order to reduce the inflationary pressure. If the opposite occurs
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the rule recommends a lower nominal short term interest rate in order to stimulate
consumption and investment.
Although Taylor (1993) shows that the rule describes the federal funds rate
quite accurate in the period 1987-1992, there are some arguments why the rule might
not accurately describe the behaviour of a central bank. First of all, the main two
objectives of the Fed, referred as the FOMC’s dual mandate, are full employment and
price stability. Therefore, the output gap might be less relevant for the Fed than the
unemployment gap. Secondly, Svensson (2003) states that even if the central bank’s
objective is to stabilize inflation and output a simple Taylor rule will be suboptimal.
The reason is that the impact of interest rate changes on inflation and output (or
unemployment) comes with a lag. Therefore, Svensson (2003) argues that the value of
the instrument has to be set consistently with the inflation target and output forecasts
allowing the use of judgement and what he calls extra-model information. In other
words, the central bank’s behaviour should be forward looking. Besides this
theoretical argument there is also a practical argument, namely that actual inflation and
the output are not known when the Fed sets its federal funds rate target. As a result,
the rule should be based on expected inflation and output instead of the realized
values.
In order to deal with the two mentioned issues in the empirical model, the
output gap will be replaced for the unemployment gap (using Okun’s Law) and we
substitute the realized values of the explanatory variables for the expected values.
Despite that this rule is forward looking and includes the FOMC’s dual mandate; it
still misses a well observed behaviour of the Fed which is commonly known as
interest rate smoothing. Interest rate smoothing reduces the variability of interest rate
change. Following Sack and Wieland (2000), the main reasons for interest rate
smoothing are to avoid measurement errors in real time data of key macroeconomic
variables, reduce uncertainty about outcomes of relevant structural parameters, and
facilitate the forward looking expectations of agents in the market. Additional,
Woodford (1999) claims that interest rate smoothing is one of the conditions in order
to achieve optimal monetary policy. Although interest rate smoothing is widely
accepted, the standard Taylor rule does not include this. One way to include interest
rate smoothing, which is also done among others by Clarida et al. (2000) and
Woodford (1999), is to weigh the lagged variable and the interest rate target. In
mathematical way it can be written as a partial adjustment model:
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= + 1 − ∗
(2)
∗ ∗ = + − ∗ + − (3)
Here is the actual federal funds rate, is the lagged federal funds rate, and ∗ is
the federal funds rate target based on the modified Taylor rule shown by Equation (3).
In addition, measures the degree of interest rate smoothing. When is relatively
high, the Fed tends set the new federal funds rate relatively close to the lagged federal
funds rate and therefore the degree of interest rate smoothing is high. Moreover, the
opposite shows that the degree of interest rate smoothing is relatively low. According
to Rudebusch (2002) most values of are in the range of 0.8. In addition, Kim and
Nelson (2006) use a time-varying model also find an around 0.8 in the period 19702001. In the partial adjustment model the errors are serially correlated which biases the
LS standard errors. So, we take a different approach instead and model policy inertia
by applying Generalized Least Squares (GLS) with AR(1)-coefficient ρ, and timevarying weights:
= + 1 − + − ∗ − − ∗ +
∗ − − − ∗ + (4)
The reason for time-varying weights is that we will obtain the coefficients and as
a time series, which is helpful to test the political pressure theories of Hibbs (1987)
and Nordhaus (1975). In order to make the coefficients and time-varying, a state
space model with the Kalman filter will be used. State space models mainly have two
useful applications for macroeconomic. Firstly, it can identify unobserved variables,
such as natural rate of unemployment or the potential level of output. Secondly, it can
be used to make coefficients time-varying. Our state space model representation
consists of Equation (4) above completed with:
= + !
= + (5)
(6)
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Equation (4) represents the Fed’s interest rate policy where is the error term, and
where is called the signal variable. In addition Equations (5) and (6) model and
!
as stochastic processes with error terms and . Different stochastic processes
can been chosen for the state variables, we choose random walk processes without
drift that allow for slowly evolving weights in the Taylor rule.
The main feature of a state space model is the Kalman filter (Kalman, 1960). In
short, the Kalman filter basically predicts the value of the future state variable ( and
) based on the information given at the previous period t-1. After this the Kalman
filter updates the predicted estimates when the value of the signal variable ( ) is
known and gives a filtered estimate of the state variables ( and ). This will be an
iterative process until the end of the sample. After that it will give a smoothed
estimated which are calculated on the whole information set by backward calculations,
so it estimates the state value at time t-1 based on the information of the state and
signal variables given at time t which is obtained by the iterative process described
before. Thus, most information is contained in the smoothed estimates, which will be
used in our approach. One additional beneficial feature of the Kalman filter is that it
can be used with different frequencies of the data in the states variables. Therefore, the
monthly expectations of inflation and the quarterly expectations of the unemployment
rate can be used.
The inflation target of the Fed will be assumed to be 2% over the entire
period. This assumption is in accordance with Taylor (1993). Although Fed’s inflation
targets may vary over time due to different economic circumstances, the target of 2%
may be the ideal value of the Fed, and therefore a reasonable assumption.
3.2
Political pressure
After obtaining the smoothed time series of and by using the Kalman filter, we
test the political monetary cycle theory and the partisan theory. As already mentioned,
the political monetary cycle is based the concept of an economic boost before the
election and a recession after the election with no difference with respect to the
partisan affiliation of the incumbent. In order to test this theory we add three election
(0,1) dummies: an election dummy (E), a before-election dummy (B), and an afterelection dummy (A). In the next section we discuss how we construct the dummy
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variables. Following the theory, an economic boost before the election would let the
Fed react less to inflation and more to the unemployment gap. On the other hand, after
the elections the Fed should be less responsive to the unemployment gap and be more
inflation averse.
To test the partisan theory we construct a partisan-dummy P with the value of 1
when a Democrat is in the office while it will be 0 when a Republican is in charge.
The partisan theory describes that Republicans are more inflation avers while the
Democrats care more about unemployment. These tests will reveal whether there is
significant pressure of the incumbent on the Fed to change their behaviour toward the
federal funds rate. However, when the Fed is completely independent from the White
house both theories should be rejected. The equations to test these theories are:
Δ = + # $ + % + & ' + ( ) + *
(7)
!
Δ = + + , $ + - + . ' + ) + *
(8)
Following the theory, an economic boost before the election would let the Fed react
less to inflation and more to the unemployment gap. As a result, the coefficients #
and , should be negative. On the other hand, after the elections the Fed should be less
response for the unemployment gap and be more inflation averse. Hence, the
coefficients & and . should be positive. The partisan theory describes that
Republicans are more inflation avers while the Democrats care more about
unemployment. Consequently, ( should be negative because Democrats are less
inflation fighters and should also negative because they react heavier to high
unemployment.
4.
Data
We are analysing political pressure for the period August 1987 until and including
January 2006. In this period monetary policy has been well developed and the Fed was
led by one chairman. Table 1 gives a description of the time series used in this paper.
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Table 1. Descriptions and sources of the time series.
Series name
Description
FFR
Effective Federal Funds Rate
Source: Board of Governors of the Federal Reserve System
EXI
Median expected price change next 12 months
Source: Survey of the University of Michigan
EXU
Median 4-quarter ahead unemployment forecast (sequence of 5step-ahead forecasts including current-quarter forecasts)
Source: Survey of professional forecasters of the Federal Bank of
Philadelphia
The definitions, samples, frequency, and sources of these series are in
Appendix A. The effective federal funds rate is from the Board of Governors of the
Federal Reserve System. These are annualized monthly averages based on daily
figures. The survey of the University of Michigan has been used to obtain the expected
yearly inflation rate for every month. The expected 12 month ahead inflation rate is
less volatile than the actual annual inflation rate as is shown in Figure 1. The quarterly
expected unemployment rate is from a survey of professional forecasters of the
Federal Bank of Philadelphia. Figure 2 reveals that the expected 4-quarter ahead
forecast of unemployment underestimates the peaks and troughs in the actual
unemployment rate. These peaks and troughs in the actual unemployment rate for the
US correspond closely to the peaks (July 1990 and March 2001) and troughs (March
1991 and November 2001) in the US business cycle as dated by the NBER.
Instead of assuming a constant natural unemployment rate of for instance 6%,
we use the Hodrick-Prescott filter because the Fed might target a different rate under
different economic circumstances. The quarterly expected unemployment rate is
decomposed in a monthly trend component, which we interpret as the expected natural
rate of unemployment, and a cyclical component using a state space approach of the
Hodrick-Prescott filter using a wider sample (July 1954 until and including June 2013)
to avoid the end-point bias. We denote by the expected unemployment gap the
difference between the median 4-quarter ahead forecast (EXU) and the smoothed
monthly trend component (EXUHPF) from the Hodrick-Prescott filter. Finally, the
target level of the inflation is set at 2% annually, and the expected inflation gap is
11
defined as the median expected price change in the next 12 months (EXI) minus 2.
These constructed series are presented in Figure 3.
7
Median expected 12 month ahead inflation rate
Actual annual inflation (CPI; US Bureau of Labor Statistics)
6
5
4
3
2
1
0
1988
1990
1992
1994
1996
1998
2000
2002
2004
Figure 1. The median expected 12 month ahead inflation rate and the actual annual
inflation rate.
8
Median 4-quarter ahead forecast of unemployment
Unemployment (US Bureau of Labor Statistics)
7
6
5
4
3
1988
1990
1992
1994
1996
1998
2000
2002
2004
Figure 2. The median expected 4-quarter ahead forecast of unemployment and the
actual unemployment rate.
12
FFR
10
8
6
2
0
Reagan
4
88
GHW Bush
90
92
GW Bush
Clinton
94
96
98
00
02
04
98
00
02
04
00
02
04
EXI-2
3
2
1
0
-1
-2
88
90
92
94
96
EXU-EXUHPF
1.5
1.0
0.5
0.0
-0.5
-1.0
88
90
92
94
96
98
Figure 3. The federal funds interest rate (FFR), the expected inflation rate minus the
target inflation rate (EXI-2), and the expected unemployment rate minus the expected
natural rate of unemployment (EXU-EXUHPF) for the period August 1987-January
2006.
13
Instead of assuming a constant natural unemployment rate of for instance 6%,
we use the Hodrick-Prescott filter because the Fed might target a different rate under
different economic circumstances. The quarterly expected unemployment rate is
decomposed in a monthly trend component, which we interpret as the expected natural
rate of unemployment, and a cyclical component using a state space approach of the
Hodrick-Prescott filter using a wider sample (July 1954 until and including June 2013)
to avoid the end-point bias. We denote by the expected unemployment gap the
difference between the median 4-quarter ahead forecast (EXU) and the smoothed
monthly trend component (EXUHPF) from the Hodrick-Prescott filter. Finally, the
target level of the inflation is set at 2% annually, and the expected inflation gap is
defined as the median expected price change in the next 12 months (EXI) minus 2.
The time series are illustrated in Figure 3.
In the analysis we focus exclusively on the Greenspan era: August 1987 until
and including January 2006. In this period there were five elections with 8 years of
Democrats (Clinton administrations, February 1993 – January 2001) and 10.5 years of
Republicans in the office (Reagan, February 1981-January 1989; G.H.W. Bush,
February 1989-January 1993; and G.W. Bush, February 2001-January 2009). Figure 3
illustrates that in the administration of G.H.W. Bush and the first administration of
G.W. Bush the federal funds rate declined sharply. In the period 1999-2000 the
interest rate was raised in six steps from 4.5% to 6.5%. However, over the period
2000-2001 the stock market dropped sharply, and as a response the Fed reduces the
federal funds rate dramatically. In addition, the Fed kept the federal funds rate
extremely low until 2004.
To test the political pressure hypotheses we construct dummy variables. The
dummy variable P has a value of is 1 in the months in which the Democrats are in
office and zeroes for Republicans. Furthermore, we constructed three (0,1) election
dummy variables: E is 1 in the election month (November), and 0 elsewhere. B and A
have ones in six months before, respectively after the elections, and 0 elsewhere.
Obviously, six months is an arbitrary choice. However, we indicate below that
different assumptions do not affect the results.
14
5.
Results
The economic model given by Equations (4), (5), and (6) is estimated using maximum
likelihood. We impose some assumptions on the model. The signal equation (4), and
the state equations (5) and (6) all contain an error term. We include an error term in
the signal equation so that the weights in the Taylor rule equation do not vary a lot.
The underlying assumption is that central bank behaviour is not expected to be very
erratic. We also assume that the covariance between the error terms is zero.1
Furthermore, we set the coefficients at initial values. The initial values for the
autocorrelation coefficient ρ and nominal target interest rate c0 are set at 0.9 and 4,
respectively. The autocorrelation coefficient is initially chosen close to the first-order
autocorrelation coefficient of the federal funds rate. The initial value for the nominal
target interest rate is based on an real interest rate of 2% and 2% inflation. 2 The
specification of the error variances facilitate positive error variances.3
Table 2 shows the initial values for the coefficients and their estimates. The
coefficients of the interest rate equation are significant at 5%, and the estimate for the
autocorrelation coefficient is smaller than 1 (p-value = 0.011). The initial state vector
(α0, β0)ʹ = (0, 0)ʹ, and the final state vector (α, β)ʹ = (0.023, -1.469)ʹ with a final state
 0.051 0.002 
covariance matrix 
 .
 0.002 0.399 
Figure 4 displays the time series of the smoothed time-varying coefficients of
the expected inflation gap and the expected unemployment gap (coefficients and
) from August 1987 until January 2006. Figure 4 shows that signs of the coefficients
are as expected, but the final state value of is statistically not different from 0. It is
also clear that the weight for the unemployment gap in the Taylor rule gradually
1
Allowing the covariance between the errors in the state equations to be non-
zero results in the covariance to be not significantly different from zero, but the
results differ.
2
The results are not very sensitive for the initial values. Only if the initial value
for the autocorrelation coefficient is smaller than 0.25, the results differ, but the
information criteria (Akaike and Schwarz) go up and the model is less
informative.
3
Different initial values do not change the results.
15
increases until the start of the G.W. Bush administration. The weight on inflation
gradually drops until 2001 which coincides with the end of the Internet bubble.
Table 2. Estimates of the state space model (August 1987-January 2006).
Model specification:
= + 1 − + − ∗ − − ∗ +
∗ − − − ∗ + ;
!
= + ; = + Coefficient
Initial value
Estimate (se)
ρ
0.9
0.922 (0.031)
c0
4
3.532 (1.097)
Error variances = exp(c)
Initial value for c
Estimate for c (se)
ε
-1
-1.116 (0.172)
εα
-1
-5.998 (1.976)
εβ
-1
-5.301 (3.276)
Final state
p-value
α
0.023
0.918
β
-1.469
0.020
Observations (quarterly)
74
Log likelihood
-81.819
0.8
Coefficient for the expected inflation gap
Coefficient for the expected unemployment gap
0.4
0.0
-0.4
-1.2
-1.6
Reagan
-0.8
1988
GHW Bush
1990
1992
Clinton
1994
1996
1998
GW Bush
2000
2002
2004
Figure 4. The smoothed time-varying coefficients of the expected inflation gap and the
expected unemployment gap.
16
It may be informative to analyze the correlations between the federal funds
rate, the expected unemployment gap, the expected inflation gap, the time-varying
coefficient of the expected unemployment gap and the time-varying coefficient of the
expected inflation gap. From Table 3 we conclude that the correlation between the
expected inflation gap and the federal funds rate is positive, and the correlation
between the expected unemployment gap and the federal funds rate is negative. This is
what we expect: a higher inflation gap correlates with a higher federal funds rate, and
a lower unemployment gap also correlates positively with federal funds rate.
Table 3. Correlations between the federal funds rate (FFR), the expected
unemployment gap (EXU-EXUHPF), the expected inflation gap (EXI-2), the timevarying coefficient of the expected inflation gap (α), and the time-varying coefficient of
the expected unemployment gap (β) for the period August 1987-January 2006.
FFR
EXU-EXUHPF
EXI-2
State α State β
FFR
1.000
EXU-EXUHPF
-0.650 1.000
EXI-2
0.619 -0.508
1.000
State α
0.680 -0.179
-0.535
1.000
State β
0.727 -0.209
-0.500
0.979
1.000
Table 3 also shows that the correlation between the coefficients of the gapterms is strong and positive. One might expect the correlation to be negative if the
policy consistently increases one coefficient while lowering the other. This is only
observed for the G.W. Bush administration. Finally, the coefficients correlate
positively with the federal funds rate.
The model is estimated until January 2006. Figure C1 in Appendix shows
dynamic forecasts without using additional information about the federal funds rate,
but with actual data on unemployment, trend unemployment and inflation gap. With
the end-of-sample weights in the Taylor rule equation, the Taylor rule tracks the
federal funds rate remarkably well until 2010. This forecast error is remarkably small
since the forecast period includes the build-up of the US housing bubble, its burst, the
ensuing credit crisis and the 2007-2009 recession in the United States. After 2010, the
Taylor rule overestimates the federal funds rate by about 0.6%.
17
6.
Political pressure
In this section we test the existence of the political monetary cycle and partisan
affiliation for the period in which Greenspan served as Chairman of the Federal
Reserve of the United States from August 1987 to January 2006.
The state variables and are assumed to be random walk processes with
!
error terms and . The differences of these random walk processes are stationary
variables which are used to test for impact of political pressure on the weights in the
Taylor rule. We add election dummies to test for monetary cycles and a dummy for
political affiliation of the incumbent president to test for partisan effects.
Table 4. Estimates of political pressure (August 1987-January 2006).
100Δ = + # $ + % + & ' 100Δ = + + , $ + - + . '
!
+ ( ) + *
Variable
Coefficient
se
+ ) + *
Coefficient
se
intercept
-0.185
0.033
-0.376
0.026
B (6 months)
-0.063
0.066
-0.083
E
-0.035
0.148
0.019
0.116
A (6 months)
0.031
0.065
-0.000
0.051
P
-0.285
0.046
-0.021
0.036
Observations
221
221
R-squared
0.154
0.013
Table 4 shows that over the period August 1987 to January 2006 the weights in
the Taylor rule gradually drop, this implies a stronger emphasis on reducing
unemployment and less emphasis on reducing inflation. There is also evidence for a
partisan effect. Under Democratic presidents the weight on the expected inflation gap
drops considerably (-0.285), and this is statistically significant at 1% while the weight
on expected unemployment in the Taylor rule does not depend on the political
affiliation of the incumbent president. The dummies B and A reflect political pressure
six months before and 6 months after the elections, respectively. Evidence for an
18
election driven monetary cycle is absent since none of the dummies is statistically
significant at conventional levels of significance. Using other dummies – single (0,1)
dummies up to 12 months or dummies for different time spans – does not change this
result.
7.
Conclusion
In order to test for political pressure the Fed’s reaction function is modeled for the
period August 1987 to January 2006 by a modified time-varying Taylor rule
specification. The coefficients of the expected inflation gap and the expected
unemployment gap are made time-varying by using the Kalman filter in a state space
setting.
The main political macroeconomic theories of an election driven monetary
cycle and the partisan affiliation theory are tested, and we found no evidence for an
opportunistic political monetary cycle. However, we did find evidence of an effect of
partisan affiliation of the incumbent president. We show that the Fed has been less
inflation avers when a Democrat president is in office.
There are some limitations of the study. First of all, the inflation target of 2%
of the Fed may not be always representing the actual target. Secondly, there may be
omitted variables such as financial stress indicators, which are not taken in account in
the model explicitly. Finally, although state space models have clear advantages which are stressed in this paper - there are disadvantages as well; there is a great
variety of state space models formulations, and the outcomes may be sensitive to
initial conditions. This flexibility is an advantage when used carefully. Another
characteristic of state space models is that you have to have prior knowledge about the
processes you are modeling.
19
References
Abrams, B. A. and P. Iossifov (2006), “Does the Fed Contribute to a Political Business
Cycle?,” Public Choice, vol. 129(3), pp. 249-262.
Alesina, A. F. (1987), “Macroeconomic Policy in a Two-Party System as a Repeated
Game,” The Quarterly Journal of Economics, vol. 102(3), pp. 651-678.
Alesina, A. and J. Sachs (1988), “Political Parties and the Business Cycle in the
United States, 1948-1984,” Journal of Money, Credit and Banking, vol. 20(1),
pp. 63-82.
Alesina, A. and L. H. Summers (1993), “Central Bank Independence and
Macroeconomic Performance: Some Comparative Evidence,” Journal of
Money, Credit and Banking, vol. 25(2), pp. 151-162.
Alesina, A., N. Roubini, and G. D. Cohen (1997), Political Cycles and the
Macroeconomy, Cambridge Mass, The MIT Press, Cambridge MA.
Barro, R., (1998), Determinants of Economic Growth: A Cross-Country Empirical
Study, The MIT Press, Cambridge MA.
Barro, R. and D. Gordon (1983), “Rules, discretion and reputation in a model of
monetary policy,” Journal of Monetary Economics, vol. 12(1), pp. 101-121.
Beck, N. (1984), “Domestic Political Sources of American Monetary Policy: 195582,” The Journal of Politics, vol. 46(3), pp. 786-817.
Beck, N. (1987), “Elections and the Fed: Is There a Political Monetary Cycle?,”
American Journal of Political Science, vol. 31(1), pp. 194-216.
Caporale, T. and K. B. Grier (1998), “A Political Model of Monetary Policy with
Application to the Real Fed Funds Rate,” Journal of Law and Economics, vol.
41(2), pp. 409-428.
Cargill, T. F. and G. P. O’Driscoll (2012). “Measuring Central Bank Independence,
Policy Implications, and Federal Reserve Independence,” Paper presented at
the American Economic Association.
Cargill, T. F. and G. P. O’Driscoll (2013). “Federal Reserve Independence: Reality or
Myth?,” Cato Journal, vol. 33(3), pp. 417-435.
Chappell, H. W., T. M. Havrilesky, and R. R. McGregor (1993), “Partisan Monetary
Policies: Presidential Influence through the Power of Appointment,” The
Quarterly Journal of Economics, vol. 108(1), pp. 185-218.
20
Chappell, H. W. and W. Keech (1986), “Party Differences in Macroeconomic Policies
and Outcomes,” American Economic Review, vol. 76(2), pp. 71-74.
Clarida, R., J. Galí, and M. Gertler (2000), “Monetary Policy Rules And
Macroeconomic Stability: Evidence And Some Theory,” The Quarterly
Journal of Economics, vol. 115(1), pp. 147-180.
Corder, J. K. (2006), “Partisan politics and Fed policy choices: A Taylor rule
approach,’’ Prepared for presentation at the Annual Meetings of the Midwest
Political Science Association, pp. 1-21.
Cukierman, A., P. Kalaitzidakis, L. Summers, and S. B. Webb (1993), “Central bank
independence, growth, investment, and real rates,” Carnegie-Rochester
Conference Series on Public Policy, vol. 39 (1), pp. 95-140.
Cukierman, A. and A. H. Meltzer (1986), “A Theory of Ambiguity, Credibility, and
Inflation under Discretion and Asymmetric Information,” Econometrica, vol.
54(5), pp. 1099-1128.
Cukierman, A., S. B. Webb, and B. Neyapti (1992), “Measuring the Independence of
Central Banks and Its Effect on Policy Outcomes,” World Bank Economic
Review, vol. 6(3), pp. 353-398.
Faust, J. and J. Irons (1999), “Money, politics and the post-war business cycle,”
Journal of Monetary Economics, vol. 43(1), pp. 61-89.
Fischer, S. (1993), “The role of macroeconomic factors in growth,” Journal of
Monetary Economics, vol. 32(3), pp. 485-512.
Grier, K. B. (1984), The Political Economy of Monetary Policy, doctoral dissertation.
Department of Economics, Washington University, St. Louis, MO.
Grier, K. B. (1989), “On the Existence of a Political Monetary Cycle,” American
Journal of Political Science, vol. 33(2), pp. 376-389.
Grilli, V., D. Masciandaro, G. Tabellini, M. Malinvaud, and M. Pagano (1991),
“Political and Monetary Institutions and Public Financial Policies in the
Industrial Countries,” Economic Policy, vol. 6(13), pp. 342-392.
Havrilesky, T. M. (1987), “A Partisanship Theory of Fiscal and Monetary Regimes,”
Journal of Money, Credit and Banking, vol. 19(3), pp. 308-325.
Hayo, B. and C. Hefeker (2002), “Reconsidering central bank dependence,” European
Journal of Political Economy, vol. 18(4), pp. 653-674.
Hibbs, D. (1987), “The American political economy: Macroeconomics and electoral
politics,” Harvard university press, Cambridge MA.
21
Kalman, R. E. (1960), “A New Approach to Linear Filtering and Prediction
Problems,” Journal of Basic Engineering, vol. 82(1), pp. 35-45.
Kiewiet, D. R. and D. Rivers (1984), “A retrospective on retrospective voting,”
Political behavior, vol. 6(4), pp. 369-393.
Kim, C. J. and C. R. Nelson (2006), “Estimation of a forward-looking monetary policy
rule: A time-varying parameter model using ex post data,” Journal of
Monetary Economics, vol. 53(8), pp. 1949-1966.
Kydland, F. E. and E. C. Prescott (1977), “Rules Rather Than Discretion: The
Inconsistency of Optimal Plans,” Journal of Political Economy, vol. 85(3), pp.
473-491.
McCallum, B. T. (1978), “The Political Business Cycle: An Empirical Test,” Southern
Economic Journal, vol. 44(3), pp. 504-515.
Nordhaus, W. D. (1975), “The Political Business Cycle,” Review of Economic Studies,
vol. 42(2), pp. 169-190.
Ravn, M. and H. Uhlig (2002), “On adjusting the Hodrick-Prescott filter for the
frequency of observations,” The Review of Economics and Statistics, vol.84(2),
pp. 371-375.
Rogoff, K. (1985), “The Optimal Degree of Commitment to an Intermediate Monetary
Target,” The Quarterly Journal of Economics, vol. 100(4), pp. 1169-1189.
Rogoff, K. and A. Sibert (1988), “Elections and Macroeconomic Policy Cycles,”
Review of Economic Studies, vol. 55(1), pp. 1-16.
Rudebusch, G. D. (2002), “Term structure evidence on interest rate smoothing and
monetary policy inertia,” Journal of Monetary Economics, vol. 49(6), pp.
1161-1187.
Sack, B. and V. Wieland (2000), “Interest-rate smoothing and optimal monetary
policy: a review of recent empirical evidence,” Journal of Economics and
Business, vol. 52(1 and 2), pp. 205-228.
Svensson, L. E. O. (2003), “What Is Wrong with Taylor Rules? Using Judgment in
Monetary Policy through Targeting Rules,” Journal of Economic Literature,
vol. 41(2), pp. 426-477, June.
Taylor, J.B. (1993), “Discretion versus policy rules in practice,” Carnegie-Rochester
Conference Series on Public Policy, vol. 39(1), pp. 195-214.
Taylor, J.B. (2013), “The Effectiveness of Central Bank Independence vs. Policy
Rules,” Business Economics, vol. 48(3), pp. 155-162.
22
Temple, J. (2000), “Inflation and Growth: Stories Short and Tall,” Journal of
Economic Surveys, vol. 14(4), pp. 395-426.
Tempelman, J. H. (2007), “A commentary on ‘Does the Fed contribute to a political
business cycle?’,” Public Choice, vol. 132(3), pp. 433-436.
Woodford, M. (1999), “Optimal Monetary Policy Inertia,” Manchester School,
University of Manchester, vol. 67(s1), pp. 1-35.
23
Appendix A. Data: definitions and sources
Table A1. Series names, definitions, samples and sources.
Series name
Description
Sample, units and
Source
frequency
FFR
EXI
Effective Federal Funds Rate
1954M7-2013M6
FRED (Federal
(Monthly; Percent;
Reserve Economic
Averages of Daily
Data); Board of
Figures; Not
Governors of the
Seasonally
Federal Reserve
Adjusted)
System
Median expected price change
1978M1-2013M5
FRED; Thomson
next 12 months
(Monthly; Percent;
Reuters/University of
Not Seasonally
Michigan
Adjusted)
EXU
E
Median Forecast, 4-quarter
1968Q4-2013Q2
Federal Reserve Bank
ahead unemployment forecast
(Quarterly;
of Philadelphia;
(sequence of 5-step-ahead
Percentage points;
Survey of Professional
forecasts including current-
Seasonally
Forecasters
quarter forecasts)
Adjusted)
Election (0,1)-dummy: 1 in
1954M7-2013M3
election month (November), 0
elsewhere
B
Pre-election period
1954M7-2013M3
(0,1)-dummy: 1’s six months
before elections, 0 elsewhere
A
Post-election period
1954M7-2013M3
(0,1)-dummy: 1’s six months
after elections, 0 elsewhere
P
(0,1)-dummy: 1 for a Democrat;
1954M7-2013M3
0 for Republican
24
Appendix B. Calculating trend unemployment
EXU is decomposed in a growth or trend component (EXUHP) and stationary residual
or cyclical component using the Hodrick Prescott filter which we estimate by the
maximum likelihood using the Kalman filter. The state space formulation is
= / + (B1)
/ = 2/ − /# + ,
(B2)
where / is the trend component and the cyclical component has mean 0. The ratio
of variances between and is λ in the Hodrick Prescott filter function. We use as
smoothing parameter λ = 129600. This is based on the frequency rule in Ravn-Uhlig
(2002) with power=4. The variance of the residual noise term is lower if λ is higher.
Figure B1 shows expected unemployment (EXU) and the trend component
from the smoothed Kalman filter (EXUHPF). The monthly cyclical component is
calculated as EXU minus the smoothed state variable EXUHPF.
10
EXU
EXUHPF
9
8
7
6
5
4
3
1970
1975
1980
1985
1990
1995
2000
2005
2010
Figure B1. The expected unemployment (EXU) and the trend component from the
smoothed Kalman filter (EXUHPF) for the period 1969M01-2013M07.
25
Appendix C. Dynamic forecasts
10
Federal funds rate (FFR)
Dynamic forecast of the FFR
8
6
4
2
0
-2
90
92
94
96
98
00
02
04
06
08
10
12
Figure C1. Dynamic forecast for the period February 2006 to July 2013.
26
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4